Robotics funding has broadly eased since its peaks in 2021-2022, but many of the issues exposed by the pandemic remain constant. The biggest driver behind venture funding in the category is the ongoing labor shortage. Analyst Garner predicts that by 2028half of large businesses will use robots in their warehouse and manufacturing processes.
The other key factor that warehouse/logistics robotics strives for is a proven track record. While many approaches to automation currently have a theoretical ROI, warehouse robots are out there doing the job right now, from Amazon on down.
Gray matter is among those with a proven track record in the field. The Southern California company says its systems currently produce “a 2~4x improvement in production line productivity [and a] 30% or more reduction in disposable waste’. Big names including 3M currently use its systems.
All this despite the fact that GrayMatter is a new company, founded just at the beginning of the pandemic in 2020.
“We founded GrayMatter to boost productivity while prioritizing workforce well-being,” co-founder and CEO Ariyan Kabir says in a statement. “With our physics-based AI systems, we are fulfilling our mission while unlocking new levels of performance and productivity. With the support of our investors, we are making a real difference for workers in stores and addressing the critical workforce shortages in manufacturing today.”
So what is a “physics-based” robotic system? GrayMatter contrasts its approach with the purely data-driven method used by others. The company explains:
Consider the problem of predicting the output of the process based on the input. If the output is expected to increase as the input increases, then the underlying model space is limited and a smaller amount of data can train it. We do not need to consider arbitrarily complex models. On the other hand, this requires more complex representations and associated solution generation methods to handle constraints to produce acceptable computational performance. We cannot train a simple neural network with observed input and output data. In this case, there is no guarantee that it will preserve the process constraint if the output used during training is noisy.
Interest in the company spurred growth. GrayMatter is a regular in robotics job postings. The roundup we published in May listed 20 open roles, among the highest of those listed.
This growth, in turn, is supported by continued funding. On Thursday, GrayMatter announced a $45 million Series B round led by Wellington Management, with participation from NGP Capital, Euclidean Capital, Advance Venture Partners, SQN Venture Partners, 3M Ventures, B Capital, Bow Capital, Calibrate Ventures, OCA Ventures and Swift Entrepreneurs. The round nearly doubles the $25 million Series A the company closed in 2022.
